Accurate sales forecasting is important to the fashion enterprise, such as apparel and accessories, handbags, wallets. However, it is a challenging problem since the requirements from consumers can be influenced by many factors. In this paper, the sales are forecasted based on an improved multidimensional grey model (IGM(1,N)) and artificial neural network (ANN), where the multi-dimensional grey model is used to model sales data while the neural network is used to correct the errors. The advantage of the proposed hybrid model is that it considers the relation between the sales and the factors that influence the customer requirements. The performance of the proposed hybrid model is evaluated with sales data from Ali-TianMao, and the experimental results demonstrate that the proposed hybrid model is superior to the existing sales forecasting models.